Detecting and responding to data loss events in a dispersed storage network

ABSTRACT

A method for use in a dispersed storage network operates to identify missing, out-of-date or otherwise compromised encoded data slices in a dispersed storage network (DSN), and when a decode threshold of encoded data slices is not available to rebuild an associated data object, determine whether a data loss event has occurred. When a data loss event is determined to have occurred the method continues by initiating a process to recover all or some of the lost data and may include notification to DSN entities that a data loss event has occurred.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention; and

FIG. 10 is a flowchart illustrating an example of detecting, notifyingand recovery from a data loss event in a dispersed or distributedstorage network (DSN) in accordance with the present invention;

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 and 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data (e.g., data 40) as subsequently described withreference to one or more of FIGS. 3-8. In this example embodiment,computing device 16 functions as a dispersed storage processing agentfor computing device 14. In this role, computing device 16 dispersedstorage error encodes and decodes data on behalf of computing device 14.With the use of dispersed storage error encoding and decoding, the DSN10 is tolerant of a significant number of storage unit failures (thenumber of failures is based on parameters of the dispersed storage errorencoding function) without loss of data and without the need for aredundant or backup copies of the data. Further, the DSN 10 stores datafor an indefinite period of time without data loss and in a securemanner (e.g., the system is very resistant to unauthorized attempts ataccessing the data).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The managing unit 18 creates and stores user profile information (e.g.,an access control list (ACL)) in local memory and/or within memory ofthe DSN memory 22. The user profile information includes authenticationinformation, permissions, and/or the security parameters. The securityparameters may include encryption/decryption scheme, one or moreencryption keys, key generation scheme, and/or data encoding/decodingscheme.

The managing unit 18 creates billing information for a particular user,a user group, a vault access, public vault access, etc. For instance,the managing unit 18 tracks the number of times a user accesses anon-public vault and/or public vaults, which can be used to generate aper-access billing information. In another instance, the managing unit18 tracks the amount of data stored and/or retrieved by a user deviceand/or a user group, which can be used to generate a per-data-amountbilling information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment (i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 80 is shown inFIG. 6. As shown, the slice name (SN) 80 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of another embodiment of a dispersedstorage network (DSN) that includes distributed storage and task (DST)processing unit 16 and DST integrity processing unit 20, the network 24of FIG. 1, and a set of storage units 1-8 such as DST execution (DSTE)units. The processing unit 16 can function as a dispersed storageprocessing agent for computing device 14 as described previously. Eachstorage unit 1-8 may be implemented utilizing the DST execution unit 36of FIG. 1. The DSN functions to rebuild an encoded data slice associatedwith a storage error.

In an example of operation of the rebuilding of the encoded data slice,when detecting a storage error associated with the encoded data slice(e.g., slice 2) of a set of encoded data slices (e.g., 1-8) of one ormore sets of encoded data slices stored in the set of storage units,where data is dispersed storage error encoded with a first informationdispersal algorithm (IDA to produce the one or more sets of encoded dataslices 1-8, where each set of encoded data slices includes a first IDAwidth number of slices (e.g., 8), where a first decode threshold number(e.g., 5) of encoded data slices of each set of encoded data slices isrequired to recover the data, where the first decode threshold number isgreater than half IDA width number, and where the data has been storedas another one or more sets of encoded data slices (e.g., C1-C3), wherethe data is encoded utilizing a second IDA to produce the other one ormore sets of encoded data slices C1-C3, where each set of the other setsof encoded data slices includes a second IDA width number (e.g., 3) ofslices, where a second decode threshold number (e.g., 2) of encoded dataslices of each of the other sets of encoded data slices is required torecover the data, and where the second IDA width number is less than thefirst IDA width number, the DST integrity processing unit 20 selects arecovery one or more sets of encoded data slices from the one or moresets of encoded data slices and the other one or more sets of encodeddata slices.

The detecting of the storage error includes one or more of interpretinga list slice responses, interpreting an error message, and receiving arebuilding request. For example, the DST integrity processing unit 20receives a message indicating that the slice 2 requires rebuilding. Theselecting of the recovery one or more sets of encoded data slicesincludes identifying one or more sets of encoded data slices associatedwith a decode threshold number that is less than or equal to anotherdecode threshold number associated with an alternative one or more setsof encoded data slices. For example, the DST integrity processing unit20 identifies the other slices C1-C3 when the decode threshold number is2 and the decode threshold number is 5 for the slices 1-8.

Having selected the recovery one or more sets of encoded data slices,the DST integrity processing unit 20 issues slice requests for thedecode threshold number of encoded data slices for each set of encodeddata slices of the recovery one or more sets of encoded data slices. Forexample, the DST integrity processing unit 20 identifies storage units1, 3, generates read slice requests as request slices C1, C3, and sends,via the network 24, a request slices C1, C3 to the storage units 1 and3.

Having issued the slice requests, the DST integrity processing unit 20receives the decode threshold number of encoded data slices for each setof encoded data slices of the recovery one or more sets of encoded dataslices. For example, the DST integrity processing unit 20 receives, viathe network 24, slices C1 and C3 from the storage units 1, and 3.

Having received the encoded data slices, the DST integrity processingunit 20 dispersed storage error decodes the received decode thresholdnumber of encoded data slices utilizing the second IDA for each set ofencoded data slices of the recovery one or more sets of encoded dataslices to produce recovered data. Having produced the recovered data,the DST integrity processing unit 20 dispersed storage error encodes therecover data utilizing the first IDA to produce a rebuilt encoded dataslice. For example, the DST integrity processing unit 20 dispersedstorage error encodes the recovered data to produce rebuilt encoded dataslice 2.

Having produced the rebuilt encoded data slice, the DST integrityprocessing unit 20 sends the rebuilt encoded data slice to acorresponding storage unit for storage. For example, the DST integrityprocessing unit 20 sends, the rebuilt encoded data slice 2, via thenetwork 24, to the storage unit 2 for storage.

While the DST integrity processing unit 20 is described above inconjunction with the operation of various operations, slice rebuildingmay likewise be selected in a similar fashion by a DST processing unit16 and/or managing unit 18 of FIG. 1.

FIG. 10 is a flowchart illustrating an example of detecting a data lossevent in the DSN. In particular, a method is presented for use inconjunction with one or more functions and features described inassociation with FIGS. 1-9. For example, the method can be executed by aDST integrity processing unit 20 that includes a processor andassociated memory or via another processing system of a dispersedstorage network that includes at least one processor and memory thatstores instruction that configure the processor or processors to performthe steps described below.

The method includes a step 200 where one or more processing modules(e.g., of the DST integrity processing unit 20), scan a data source formissing, out-of-date, or otherwise compromised encoded data slices. (Inpractice, the processing module may also be described in whole or inpart as a rebuild module.) Scanning (or detecting) the missing orout-of-date encoded data slices may be accomplished by a query to thetarget data source for one or more encoded data slice names (SNs). Themethod continues at step 201, where missing SN, a wrong version of anexpected SN, or an incorrect revision number of the SN would indicate aneed for rebuilding, or might indicate that a data loss event hasoccurred.

The method continues at step 203, where the processing module determineswhether a decode threshold number of encoded data slices is available.When a decode threshold number of encoded data slices is available arebuild process is initiated as described above (step 204). When adecode threshold number of encoded data slices is not available, theprocessing module will then determine (step 205) whether a data lossevent has occurred. The processing module will determine whether thedata source is undergoing a storage function process, such as a datamigration process, a transfer process, an edit process, etc. that willresolve by waiting for such process to complete (step 206) or canotherwise be resolved, such as an incomplete delete request. Incompleteor otherwise resolvable storage function processes can be described asbeing “indeterminate storage function processes”.

When the processing module determines that there no indeterminatestorage process function is ongoing, the method continues at step 207,where the processing module may then initiate a process to determinewhether there is a data loss event notification request (DLENR)associated with the data loss event, by accessing metadata associatedwith the storage unit. Metadata may be stored at one or more storagelevels, including at the container level, the vault level, as adispersed data object or in a data structure reserved for storing one ormore DLENRs. The DLENR may define a mechanism whereby a notification maybe transmitted to a particular endpoint of the DSN. The notification maybe a dsNET protocol message, an email message, an SMS message, or byother mechanisms that will be readily apparent to one skilled in theart. The notification can include details about the data loss event,including the data object affected by the data loss event, the datasource revisions affected by the data loss event, the time of discoveryof the data loss event, and an identifier of the processing module ormodules responsible for detecting the data loss event.

Once the DLENR is transmitted, one or more processing modules in the DSNmay initiate further action, including 1) initiating cross-mirror orcross-service provider rebuild operations; 2) using related sources toattempt a clean-up process; 3) initiating the repair of a particulardata object using a fixed pattern of bits; and 4) using partiallycorrupt data to meet the encoded data slice threshold. Examples mightinclude the use of various combinations of I. B and P frames to recovera video source. The DLENR may necessarily include instructions foracceptable data recovery processes.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), the method comprises: scanning a plurality of distributed storageunits to identify one or more compromised encoded data slices (EDSs) ofa set of EDSs, wherein the set of EDSs represents a first data segment;when one or more compromised EDSs of the set of EDSs is found,determining whether a decode threshold number of EDSs of the set of EDSsis available to recover the first data segment; when a decode thresholdnumber of EDSs of the set of EDSs is determined not to be available torecover the first data segment, determining whether the first datasegment is involved in an indeterminate state of processing a storagefunction; when the first data segment is involved in an indeterminatestate of processing a storage function, waiting until the processing astorage function is complete; and when the first data segment is notinvolved in an indeterminate state of processing a storage function,initiating a process to recover at least a portion of the first datasegment.
 2. The method of claim 1, wherein at least one of the one ormore processing modules of one or more computing devices of the DSN is arebuild module, and the scanning a plurality of distributed storageunits to identify one or more compromised encoded data slices isexecuted by the rebuild module.
 3. The method of claim 1 furthercomprises: determining whether there is a data loss event notificationrequest associated with the first data segment, wherein the data lossevent notification request is adapted to notify a DSN user that a dataloss event has occurred.
 4. The method of claim 3, wherein the data lossevent notification request is at least a portion of a metadataassociated with the first data segment.
 5. The method of claim 1,wherein the one or more compromised EDS are at least one of missing orinvalid EDSs.
 6. The method of claim 1, wherein the process to recoverat least a portion of the first data segment includes a least one of:determining what data object the one or more compromised EDSs are partof, determining what container the one or more compromised EDSs are partof, or determining what vault the one or more compromised EDSs are partof.
 7. The method of claim 1, wherein first data segment is a portion ofa data object and wherein the process to recover at least a portion ofthe first data segment includes one or more processing modules of one ormore computing devices of the DSN executing at least one of initiating across-mirror rebuild operation, initiating a cross-service providerrebuild operation, initiating a clean-up operation on a second datasegment associated with the data object, initiating repair of the dataobject using a fixed pattern of bits, and repairing the one or morecompromised EDSs to produce partially corrupt data.
 8. The method ofclaim 1, wherein the first data segment is a portion of a data objectand wherein the process to recover at least a portion of the first datasegment includes one or more processing modules of one or more computingdevices of the DSN rebuilding a DSN index.
 9. The method of claim 1,wherein the scanning a plurality of distributed storage units toidentify one or more compromised EDSs of a set of EDSs includescomparing expected EDS slice names to the EDS slice names of the EDSs ofa set of EDSs being scanned.
 10. The method of claim 1, wherein theindeterminate state of processing a storage function includes at leastone of an incomplete write request, an incomplete delete operation, anedit operation or a data migration operation.
 11. A computer readablememory comprises: a first memory element that stores operationalinstructions that, when executed by a computing device of a dispersedstorage network (DSN), causes the computing device to: scan a pluralityof distributed storage units to identify one or more compromised encodeddata slices (EDSs) of a set of EDSs, wherein the set of EDSs representsa first data segment; when one or more compromised EDSs of the set ofEDSs is found, determine whether a decode threshold number of EDSs ofthe set of EDSs is available to recover the first data segment; when adecode threshold number of EDSs of the set of EDSs is determined not tobe available to recover the first data segment, determine whether thefirst data segment is involved in an indeterminate state of processing astorage function; when the first data segment is involved in anindeterminate state of processing a storage function, wait until theprocessing a storage function is complete; and when the first datasegment is not involved in an indeterminate state of processing astorage function, a second memory element that stores operationalinstructions that, when executed by the computing device, causes thecomputing device to: initiate a process to recover at least a portion ofthe first data segment.
 12. The computer readable memory of claim 11,wherein the computing device of the DSN includes a rebuild module, andwherein the first memory element, when executed by the rebuild module,causes the computing device to the scan a plurality of distributedstorage units to identify one or more compromised encoded data slices.13. The computer readable memory of claim 11 further comprising:determine whether there is a data loss event notification requestassociated with the first data segment, wherein the data loss eventnotification request is adapted to notify a DSN user that a data lossevent has occurred.
 14. The computer readable memory of claim 11,wherein a data loss event notification request is at least a portion ofa metadata associated with the first data segment.
 15. The computerreadable memory of claim 11, wherein the one or more compromised EDS areat least one of missing or invalid EDSs.
 16. The computer readablememory of claim 11, wherein the process to recover at least a portion ofthe first data segment includes a least one of: determining what dataobject the one or more compromised EDSs are part of, determining whatcontainer the one or more compromised EDSs are part of, or determiningwhat vault the one or more compromised EDSs are part of.
 17. Thecomputer readable memory of claim 11, wherein first data segment is aportion of a data object and wherein the process to recover at least aportion of the first data segment includes one or more processingmodules of one or more computing devices of the DSN executing at leastone of initiating a cross-mirror rebuild operation, initiating across-service provider rebuild operation, initiating a clean-upoperation on a second data segment associated with the data object,initiating repair of the data object using a fixed pattern of bits, andrepairing the one or more compromised EDSs to produce partially corruptdata.
 18. The computer readable memory of claim 11, wherein the firstdata segment is a portion of a data object and wherein the process torecover at least a portion of the first data segment includes one ormore processing modules of one or more computing devices of the DSNrebuilding a DSN index.
 19. The computer readable memory of claim 11,wherein the first memory element that stores operational instructionsthat, when executed by a computing device of a DSN, further causes thecomputing device to compare expected EDS slice names to the EDS slicenames of the EDSs of a set of EDSs being scanned.
 20. The computerreadable memory of claim 11, wherein the indeterminate state ofprocessing a storage function includes at least one of an incompletewrite request, an incomplete delete operation, an edit operation or adata migration operation.